code: def _download_and_preprocess_data(target_dir):
      # Making path absolute
      target_dir = os.path.abspath(target_dir)
      # Conditionally download data
      archive_path = maybe_download(
          ARCHIVE_NAME, target_dir, ARCHIVE_URL
      )
      # Conditionally extract common voice data
      _maybe_extract(target_dir, ARCHIVE_DIR_NAME, archive_path)
      # Conditionally convert common voice CSV files and mp3 data to DeepSpeech CSVs and wav
      _maybe_convert_sets(target_dir, ARCHIVE_DIR_NAME)
  
file_path: DeepSpeech/bin/import_cv.py
imports: import csv
  import os
  import sys
  import subprocess
  import tarfile
  from glob import glob
  from multiprocessing import Pool
  import progressbar
  import sox
  from deepspeech_training.util.downloader import SIMPLE_BAR, maybe_download
  from deepspeech_training.util.importers import get_counter, get_imported_samples, print_import_report
  from deepspeech_training.util.importers import validate_label_eng
label_desc: Use image node_id 1 for calling a global function with example usage: _download_and_preprocess_data(target_dir) without return types